Proposal Feature Extraction. R-C3D [1]} and AFNet [2]} employ 3D RoI pooling for feature extraction and obtained low results on ActivityNet due to lack of receptive field alignment with proposal span. TAL-Net [3]}, TSA-Net [4]} employ a multi-tower network and achieve a higher performance compared with 3D RoI pooling methods. The methods of SSAD [5]}, S3D[6]}, MGG [7]}, PBRNet [8]}, MLTPN [9]}, C-TCN [10]}, RapNet [11]}, SP-TAD [12]}, and DaoTAD [13]} employ temporal feature pyramid to extract features from actions with different duration and achieved superior performance.
